Welcome message from author

This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Transcript

Research Article Digital Image Steganography Using LSB
Substitution, PVD, and EMD

Anita Pradhan , K. Raja Sekhar, and Gandharba Swain

Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Andhra Pradesh 522502, India

Correspondence should be addressed to Gandharba Swain; gswain1234@gmail.com

Received 29 March 2017; Revised 14 July 2017; Accepted 25 July 2017; Published 5 September 2018

Academic Editor: Julien Bruchon

Copyright © 2018 Anita Pradhan et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

To protect from pixel difference histogram (PDH) analysis and RS analysis, two hybrid image steganography techniques by appropriate combination of LSB substitution, pixel value differencing (PVD), and exploiting modification directions (EMD) have been proposed in this paper. The cover image is traversed in raster scan order and partitioned into blocks. The first technique operates on 2 × 2 pixel blocks and the second technique operates on 3 × 3 pixel blocks. For each block, the average pixel value difference, , is calculated. If value is greater than 15, the block is in an edge area, so a combination of LSB substitution and PVD is applied. If value is less than or equal to 15, the block is in a smooth area, so a combination of LSB substitution and EMD is applied. Each of these two techniques exists in two variants (Type 1 andType 2) with respect to two different range tables.The hiding capacities and PSNR of both the techniques are found to be improved. The results from experiments prove that PDH analysis and RS analysis cannot detect these proposed techniques.

1. Introduction

The fundamental principle of a steganography technique is to hide the secret data in image, audio, or video files [1]. Data can be hidden in images using spatial domain or frequency domain. LSB substitution is the most common technique of data hiding in spatial domain. But it can be easily detected by RS analysis [2]. To augment security in LSB substitution techniques, some precautionary measures need to be taken. The LSB planes that will carry the secret data can be selected based upon the bit pattern hidden in neighboring pixels [3]. The bits from one or more LSB planes of the pixels can be joined together to make an array. The binary data bits can be concealed in this array at appropriate portions to minimize distortion and to improve the security [4]. The PVDsteganography is another familiar data hiding technique [5]. This technique exploits the smooth areas to hide lesser number of secret bits and edge areas to hide more number of secret bits. Many variants of PVD technique have been found in literature. A technique of Khodaei and Faez uses both LSB and PVD concepts [6]. It possesses higher hiding capacity and lesser distortion. The problem in the PVD techniques is

that they are attacked by pixel difference histogram (PDH) analysis. One mechanism that addresses this problem is the adaptive range table [7, 8]. Instead of a fixed range table for all the pixels, it can be varied for every pixel. Even the number of LSB bits to be hidden in different pixels can be varied based on the smoothness of the block into which the pixel belongs to [9], so that security can be improved.

Zhang and Wang [10] proposed exploiting modification direction (EMD) steganography. The principal goal in it is that a group of secret bits be converted to a digit in (2 + 1)- ary notational system, where is the size of pixel block. This secret digit could be hidden in the pixel block by adding ±1 to only one pixel. In this technique, the hiding capacity is not good. The hiding capacity has been improved in two- stage technique in [11] and 8-ary technique in [12]. Lee et al. [13] proposed EMD technique using pixel segmentation. In a pair of pixels, each pixel is segmented into two segments. The MSB segments of the two pixels together is called the vector of coordinates (VCA) and the LSB segments of the two pixels together are called vector modification area (VMA). The bits of VCA decide about embedding. Jung and Yoo [14] proposed an EMD technique in a block of one pixel to

Hindawi Mathematical Problems in Engineering Volume 2018, Article ID 1804953, 11 pages https://doi.org/10.1155/2018/1804953

Pc P1

P2 P3

3

(c)

Figure 1: (a) Cover pixel block, (b) stego block, and (c) stego block used for extraction.

increase the hiding capacity. The EMD technique based on diamond encoding also could improve the hiding capacity [15]. Joo et al.’s EMD technique using modulus function preserved the pixel difference histogram [16]. Kim et al. [17] has proposed two EMD techniques, namely, EMD-2 and 2- EMD. In EMD-2 technique at most two pixels are modified and in 2-EMD technique, two consecutive EMDs are used. Both these techniques achieve higher hiding capacity. Wang et al. [18] said that a number of pixel groups could be combined to derive more number of embedding directions, so that distortion can be reduced. Kieu and Chang’s [19] EMD technique used eight modification directions. It fully exploited allmodification directions andmeasured the hiding capacity and distortion for different values of the parameter, . Wang et al.’s [20] EMD technique combined multiple groups to hide the data according to a designed switch map, so that the hiding capacity can be increased and distortion can be decreased. Fu et al. [21] used EMD and multilayer embedding mechanism with histogram shifting to achieve reversibility. Kim [22] advanced the EMD technique using basis vector, and (2+ − 1)-ary notational system, where and are user defined values. Shen and Huang [23] made the hiding capacity of a block adaptive by using PVD with EMD. This PVD with EMD technique provides higher hiding capacity and better PSNR. To improve upon the security keys are used to generate pseudo random num- bers, which can be used to find the embedding locations [24].

It is found that Shen and Huang’s [23] PVD with EMD technique is detectable by PDH analysis. To advance further in this paper we judiciously combined LSB substitution, PVD, and EMD techniques to protect against PDH analysis and to possess larger hiding capacity without sacrificing the PSNR. There are two techniques proposed, the first technique is designed using 2 × 2 pixel blocks and the second technique is designed using 3 × 3 pixel blocks.

2. The Proposed Technique 1 (LSB + PVD + EMD in 2 × 2 Pixel Blocks)

2.1. The Embedding Procedure

Step 1. The image is traversed in raster scan order and partitioned into nonoverlapping blocks of size 2× 2. A sample block is shown in Figure 1(a).

Step 2. For every block the average pixel value difference, = (1/3)∑3

=1 | − |, is computed. If is greater than 15, then

Table 1: Range table (Type 1).

Range, { , } 1 = {0, 7} 2 =

{8, 15} 3 =

{16, 31} 4 =

{32, 63} 5 =

{64, 127} 6 =

Range, { , } 1 = {0, 7} 2 =

{8, 15} 3 =

{16, 31} 4 =

{32, 63} 5 =

{64, 127} 6 =

3 3 4 5 6 6

the block is said to be an edge area; otherwise, it is a smooth area.

Step 3. In an edge area embedding is done using LSB substitution and PVD.

Step 4. In a smooth area embedding is done using LSB substitution and EMD.

TheLSB + PVDEmbedding Approach. The first LSB of pixel is substituted by bit 1, to act as an indicator during extraction. The other 2 LSBs are substituted by 2 data bits. A new value of this pixel

is obtained. Suppose, the decimal value of the

three LSBs of is 1 and the decimal value of the three LSBs

of is 1. A difference value df1 = 1 − 1 is calculated and

is optimized by

= {{{{ {{{{ {

+ 23, if df1 > 23−1, 0 ≤ ( + 23) ≤ 255 − 23, if df1 < −23−1, 0 ≤ ( − 23) ≤ 255 , otherwise

(1)

Now calculate three difference values, = | − | for = 1, 2, 3. It falls into one of the ranges in range table. Based on the range of , the number of bits to be hidden () can be decided. Table 1 can be referred to as Type 1 and Table 2 can be referred to as Type 2. Now convert each bits of confidential data to its decimal value for = 1, 2, 3. Then compute the new value for this difference as

= + for = 1, 2, 3.

Now for each where = 1, 2, 3, calculate two new values

Mathematical Problems in Engineering 3

= − and

= + . Select one of these two values

as by applying

= { { {

(2)

The LSB + EMD Embedding Approach. The first LSB bit of pixel is substituted by bit 0, which can act as an indicator during extraction. The other two LSBs of are substituted by two data bits. Thus, a new value

of the pixel is obtained.

Suppose, the decimal value of the three LSBs of is 1 and

the decimal value of the three LSBs of is 1. A difference

value df1 = 1 − 1 is calculated and is optimized by

(1). Suppose we denote the remaining pixels (1, 2, 3) by

a name , where = 1, 2, 3. Now apply EMD for each as follows. Each has to hide 2 bits of data. The decimal equivalent of the two data bits is . Now select from {−3, −2, −1, 0} and calculate

= + such that the

condition ( mod 4 = ) satisfies. Similarly select from

{1, 2, 3} and calculate = + such that the condition

(

mod 4 = ) satisfies. If for all the three values in list {1, 2, 3}, the condition (

mod 4 = ) does not satisfy,

then set = −10. Now calculate the stego value

for

, ) ≤ 255, −

, ) ≤ 255, −

2.2. The Extraction Procedure

Step 1. The stego image is traversed in raster scan order and partitioned into nonoverlapping blocks of size 2 × 2. Figure 1(c) represents a sample 2 × 2 stego-pixel block.

Step 2. The LSB bit of ∗ is checked, if it is 1, then for

this block the extraction procedure of LSB + PVD approach is used as follows. The next two LSBs of ∗

are extracted.

Furthermore, the ∗ = |∗ −∗ | and ∗

= ∗ − for = 1, 2, 3

are calculated, where ∗ belongs to the range and is the

lower bound of this range. Now each of these ∗ is converted

to binary bits, where is the value corresponding to the same range of ∗ . Note that the same range table (Table 1 or Table 2) which was used during embedding should be used during extraction.

Step 3. If the LSB bit of ∗ is 0, then for this block the

extraction procedure of LSB + EMD is applied as follows.The next two LSBs of∗

are extracted. For all the remaining pixels

(∗ 1 , ∗ 2 , ∗ 3 ) the decimal equivalent of the embedded bits,,

is calculated as = ∗ mod 4, for = 1, 2, 3. Now each is converted to 2 binary bits.

3. The Proposed Technique 2 (LSB + PVD + EMD in 3 × 3 Pixel Blocks)

3.1. The Embedding Procedure

Step 1. The image is traversed in raster scan order and partitioned into nonoverlapping blocks of size 3× 3. A sample block is shown in Figure 2(a).

Step 2. An average pixel value difference, = (1/8)∑8 =1 | −

|, is calculated.

Step 3. If value is greater than 15, then a combination of LSB substitution and PVD is applied.

Step 4. If value is less than or equal to 15, then a combina- tion of LSB substitution and EMD is applied.

The LSB + PVD Embedding Approach. In the central pixel, 3 LSBs are substituted by 3 data bits. A new value of the central pixel is found. Say it is

. In pixel 8 the first LSB

is substituted by bit 1, which will be used as indicator during extraction procedure.The other two LSBs in it are substituted by two data bits. After substituting, three LSBs, suppose the new value of pixel 8 is 8. The decimal value of the three LSBs of

is 1 and the decimal value of three LSBs of is

1. Similarly, the decimal value of three LSBs of 8 is 2 and

the decimal value of three LSBs of 8 is 2. Now calculate the differences df1 and df2 as, df1 = 1 − 1 and df2 = 2 − 2. Now optimize the values of

and 8 using (1) and (4), respectively.

8 = {{ {{ {

8 + 23, if df2 > 23−1, 0 ≤ (8 + 23) ≤ 255 8 − 23, if df2 < −23−1, 0 ≤ (8 − 23) ≤ 255 8 , otherwise

(4)

Now calculate seven difference values, = | − | for = 1, 2, . . . , 7. These difference values lie in one of the ranges of the range table. Table 1 can be chosen as Type 1 or Table 2 can be chosen as Type 2. Based on the range of , the number of bits to be hidden () can be decided from the range table.

Now convert each bits of confidential data to its decimal value for = 1, 2, . . . , 7. Then compute the new values for the seven differences as

= + for = 1, 2, . . . , 7. Now for

each where = 1, 2, . . . , 7, calculate two new values =

− and

= + . Select one of these two values as

by applying (2). This is the stego value of .

The LSB + EMD Embedding Approach. The first LSB of pixel 8 is substituted by 0 and the next two LSBs are substituted by two data bits. After embedding, say it is

8 . The decimal

Table 3: Results of existing techniques.

Images 512 × 512 × 3

Wu and Tsai [5] Shen and Huang [23] PSNR Capacity BPB PSNR Capacity BPB

Lena 43.67 1232606 0.999 1.56 38.01 1223062 0.998 1.55 Baboon 38.40 1403491 0.998 1.78 40.14 1343274 0.999 1.70 Peppers 43.13 1174751 0.999 1.49 41.57 1226139 0.999 1.55 Jet 43.97 1220544 0.999 1.55 43.35 1212350 0.999 1.54 Boat 41.33 1278971 0.999 1.62 41.35 1264742 0.999 1.60 House 41.27 1256404 0.999 1.59 41.75 1242081 0.999 1.57 Pot 44.01 1163700 0.999 1.47 43.38 1195641 0.999 1.52 Average 42.25 1247209 0.999 1.57 41.36 1243898 0.999 1.58

P4 P3 P2

P5 Pc P1

P6 P7 P8

(c)

Figure 2: (a) Cover pixel block, (b) stego block, and (c) stego block used for extraction.

value of the three LSBs of 8 is 2 and the decimal value of

three LSBs of8 is 2. Now calculate the difference df 2 as df2 = 2 − 2. Now optimize the value of

8 using (4).

Suppose we denote the remaining pixels (1, 2, 3, 4, 5, 6, 7, ) by a name , where = 1, 2, 3, 4, 5, 6, 7, . Now apply EMD for each as follows. Each has to hide 2 bits of data. The decimal equivalent of the two data bits is . Now select from {−3, −2, −1, 0} and calculate

= +

such that the condition ( mod 4 = ) satisfies. Similarly

select from {1, 2, 3} and calculate = + such that

the condition (

mod 4 = ) satisfies. If for all the three values in list {1, 2, 3}, the condition (

mod 4 = ) does

not satisfy, then set = −10. Now calculate

by (3). This

is the stego value of . Thus, Figure 2(b) represents the stego-pixel block.

3.2. The Extraction Procedure

Step 1. The stego image is traversed in raster scan order and partitioned into nonoverlapping blocks of size 3 × 3. Figure 2(c) represents a sample 3 × 3 stego-pixel block.

Step 2. The LSB bit of ∗ 8 is checked, if it is 1 then for this

block the extraction procedure of LSB + PVD approach is used as follows. The three LSBs of ∗

and next two LSBs

of ∗ 8 are extracted. Furthermore, the ∗

= |∗ − ∗ | and

∗ = ∗ − for = 1, 2, 3, . . . , 7 are calculated, where ∗

belongs to the range and is the lower bound of this range. Now each of these ∗

is converted to binary bits, where

is the value corresponding to the same range of ∗ . Note that the same range table (Table 1 or Table 2) which was used during embedding should be used during extraction.

Step 3. If the LSB bit of ∗ 8 is 0, then for this block the

extraction procedure of LSB + EMD is applied as follows.

The next two LSBs of ∗ 8 are extracted. For all the remaining

pixels (∗ 1 , ∗ 2 , ∗ 3 , ∗ 4 , ∗ 5 , ∗ 6 , ∗ 7 , ∗ ), the decimal equivalent

of the embedded bits, is calculated as = ∗ mod 4, for = 1, 2, 3, 4, 5, 6, 7, . Now each is converted to 2 binary bits.

4. Results and Discussion The implementation work is done using MATLAB tool and with the RGB color images. The data hiding is performed in Red, Green, and Blue planes separately. It can also be applied on gray scale images. Experiments are done with many images. Few samples are shown here. Figure 3 represents four original samples. Figures 4 and 5 are their stego samples for Type 1 and Type 2 of technique 1, respectively. Figures 6 and 7 are the stego samples for Type 1 and Type 2 of technique 2, respectively. Each stego image has hidden 700000 (seven lakhs) bits of secret data. These stego images look innocuous and no distortion is observable.

In Table 3 the results of Wu and Tsai’s PVD technique and Shen and Huang’s [23] PVD + EMD technique are given. In Tables 4 and 5, the results of the proposed technique 1 and technique 2 respectively, are given. These results are comprised of four parameters, (i) hiding capacity [1], (ii) bits per byte (BPB) [8], (iii) PSNR [1], and (iv) quality index, [6].

It can be found from Tables 3, 4, and 5 that the hiding capacity and BPB of proposed technique 1 (Type 1 and Type 2) and technique 2 (Type 1 and Type 2) are significantly enhanced as compared to that of Wu and Tsai and Shen and Huang’s techniques. Furthermore, the PSNR of the proposed technique 1 (Type 1 and Type 2) and technique 2 (Type 1 and Type 2) are nearly equal to that of Wu and Tsai and Shen and Huang’s techniques.

Mathematical Problems in Engineering 5

Table 4: Results of proposed technique 1.

Images 512 × 512 × 3

Proposed 3 PVD + 3 LSB + EMD (Type 1) Proposed 3 PVD + 3 LSB + EMD (Type 2) PSNR Capacity BPB PSNR Capacity BPB

Lena 44.45 1631063 0.999 2.07 41.33 1687353 0.999 2.15 Baboon 34.85 1898778 0.997 2.41 32.54 2237194 0.994 2.84 Peppers 40.26 1635779 0.999 2.08 38.73 1693901 0.999 2.15 Jet 42.88 1637898 0.999 2.08 42.04 1702029 0.999 2.16 Boat 38.50 1708242 0.999 2.17 36.09 1840256 0.998 2.34 House 40.23 1691500 0.999 2.15 39.18 1808544 0.998 2.30 Pot 46.35 1599030 0.999 2.03 42.80 1622565 0.999 2.06 Average 41.07 1686041 0.999 2.14 38.95 1798834 0.998 2.28

Table 5: Results of proposed technique 2.

Images 512 × 512 × 3

Proposed 7 PVD + 3 LSB + EMD (Type 1) Proposed 7 PVD + 3 LSB + EMD (Type 2) PSNR Capacity BPB PSNR Capacity BPB

Lena 44.98 1639022 0.999 2.09 41.26 1690031 0.999 2.15 Baboon 34.67 1987328 0.996 2.54 32.49 2338643 0.994 2.98 Peppers 38.14 1640887 0.998 2.09 34.70 1693278 0.997 2.16 Jet 43.00 1647786 0.999 2.10 40.46 1709098 0.998 2.18 Boat 37.76 1740611 0.998 2.22 34.36 1873870 0.997 2.39 House 40.12 1724458 0.998 2.20 38.79 1841047 0.998 2.35 Pot 43.28 1596123 0.999 2.04 38.80 1617011 0.999 2.06 Average 40.28 1710888 0.998 2.18 37.26 1823282 0.998 2.32

(a) Lena (b) Baboon (c) Boat (d) Pot

Figure 3: Original images.

6 Mathematical Problems in Engineering

Figure 5: Stego images of technique 1 (Type 2).

Figure 6: Stego images of technique 2 (Type 1).

Figure 7: Stego images of technique 2 (Type 2).

Table 6: Average results of proposed techniques.

Type BPB PSNR Proposed 3 PVD + 3 LSB + EMD (Type 1) 2.14 41.07 Proposed 7 PVD + 3 LSB + EMD (Type 1) 2.18 40.28 Proposed 3 PVD + 3 LSB + EMD (Type 2) 2.28 38.95 Proposed 7 PVD + 3 LSB + EMD (Type 2) 2.32 37.26

Furthermore, the average performance of the proposed techniques is compared with that of Kieu and Chang’s [19] technique. The average BPB and PSNR for the proposed two techniques is as given in Table 6. Similarly the BPB and PSNR of Kieu and Chang’s technique for different values of the parameter is as given in Table 7. By observing Table 6 we can find that in the proposed techniqueswith BPB values 2.14, 2.18, 2.28, and 2.32, the PSNR values are 41.07, 40.28, 38.95, and 37.26, respectively. By observing Table 7 we can find that

in the Kieu and Chang’s technique with BPB values 1, 2, 3, and 4, the PSNR values are 52.39, 46.74, 40.82, and 34.82, respec- tively. Thus, the PSNR and BPB values of Kieu and Chang’s technique (for = 6, BPB= 2.5, andPSNR=43.29) are slightly better than that of the proposed techniques (BPB = 2.32, and PSNR = 41.07). But there is no experimental evidence that Kieu and Chang’s technique is undetectable by PDH analysis and RS analysis. The proposed techniques are undetectable by PDH analysis; it is experimentally proved in Figures 9 and 10. It is also proved in Figures 11 and 12 that the proposed techniques are undetectable by RS analysis. PSNR and BPB are not only the measuring parameters; security analysis is also another parameter to be taken into consideration while judging the merit of a steganography technique.

Now let us come to security analysis. The PDH analysis diagrams clearly reveal the step effects in Shen and Huang’s technique, Figures 8(a) and 8(b). Wu and Tsai’s technique is also detected by PDH analysis, proved in [25]. But for

Mathematical Problems in Engineering 7

−40 −20 0 20 40

Pixel difference

Pixel difference

Figure 8: PDH analysis for Shen and Huang’s technique.

−40 −20 0 20 40

Pixel difference

−40 −20 0 20 40

Pixel difference

−40 −20 0 20 40

Pixel difference

−40 −20 0 20 40

Pixel difference

(d) Proposed 3 PVD + 3 LSB + EMD (Type 2)

Figure 9: PDH analysis for proposed technique 1 (Type 1 and Type 2).

8 Mathematical Problems in Engineering

−40 −20 0 20 40

Pixel difference

−40 −20 0 20 40

Pixel difference

−40 −20 0 20 40

Pixel difference

−40 −20 0 20 40

Pixel difference

(d) Proposed 7 PVD + 3 LSB + EMD (Type 2)

Figure 10: PDH analysis for proposed technique 2 (Type 1 and Type 2).

Table 7: Average results of Kieu and Chang’s technique [19].

value BPB PSNR 2 1 52.39 3 1.5 49.89 4 2 46.74 6 2.5 43.29 8 3 40.82 12 3.5 37.31 16 4 34.82 23 4.5 31.69

the proposed techniques, Figures 9(a)–9(d) and Figures 10(a)–10(d), the step effects are not observable.

We can observe the RS analysis curves of the proposed technique 1 in Figure 11. In Lena image there is bigger number of smooth blocks, but in Baboon image there is bigger number of edge blocks. For Baboon image curves for and − are linear and nearly parallel to each other.

Similarly, curves for and − are linear and nearly parallel to each other. Hence, the relation ≅ − > ≅ − is strongly satisfied. For Lena image curve for is linear and the curve for − is slightly diverging from it. Similarly, curves for are linear and the curve for − is slightly diverging from it. Hence, the relation ≅ − > ≅ − is weakly satisfied for Lena image. Figure 12 represents the RS analysis for technique 2. In all the four cases, the graphs for and − are linear and nearly overlap with one another, and the graphs for and − are linear and nearly overlap with one another. Hence, the relation ≅ − > ≅ − is strongly satisfied. Hence, it can be concluded that RS analysis cannot detect the proposed steganography techniques.

5. Conclusion

Shen and Huang proposed PVD in connection with EMD to achieve greater hiding capacity and higher PSNR. But it is found to be detectable by pixel difference histogram analysis.

Mathematical Problems in Engineering 9

50

45

40

35

30

25

20

Percentage of hiding capacity

Percentage of hiding capacity

Percentage of hiding capacity

Percentage of hiding capacity

(d) Baboon (Type 2)

Figure 11: RS analysis for Proposed technique 1 (Type 1 and Type 2).

To fix this problem, a combination of LSB substitution, PVD, and EMD is proposed in this paper. The proposed technique 1 and technique 2 operate on 2 × 2 and 3 × 3 pixel blocks, respectively, by calculating the average of the pixel value differences. Based on this average value, either PVD or EMD

is applied in combination with LSB. Both the techniques give higher hiding capacity compared to that of Shen and Huang’s technique. The recorded PSNR values are also as good as that of Shen and Huang’s technique. If we compare between the two proposed techniques, then Type 1 of technique 1 is

10 Mathematical Problems in Engineering

50

45

40

35

30

25

20

Percentage of hiding capacity

Percentage of hiding capacity

Percentage of hiding capacity

Percentage of hiding capacity

(d) Baboon (Type 2)

Figure 12: RS analysis of Proposed for proposed technique 2 (Type 1 and Type 2).

good for PSNR and Type 2 of technique 2 is good for hiding capacity. It has also been proved that the proposed techniques are not detectable by RS analysis.

Conflicts of Interest

The authors declare that they have no conflicts of interest.

References

[1] A. Cheddad, J. Condell, K. Curran, and P. Mc Kevitt, “Digital image steganography: survey and analysis of current methods,” Signal Processing, vol. 90, no. 3, pp. 727–752, 2010.

[2] J. Fridrich,M.Goljan, andR.Du, “Detecting LSB steganography in color and gray-scale images,” IEEEMultimediaMagazine, vol. 8, no. 4, pp. 22–28, 2001.

Mathematical Problems in Engineering 11

[3] G. Swain and S. K. Lenka, “A technique for secret communi- cation using a new block cipher with dynamic steganography,” International Journal of Security and its Applications, vol. 6, no. 2, pp. 1–12, 2012.

[4] G. Swain and S. K. Lenka, “A novel steganography technique by mapping words with LSB array,” International Journal of Signal and Imaging Systems Engineering, vol. 8, no. 1-2, pp. 115–122, 2015.

[5] D.-C.Wu andW.-H. Tsai, “A steganographicmethod for images by pixel-value differencing,” Pattern Recognition Letters, vol. 24, no. 9-10, pp. 1613–1626, 2003.

[6] M.Khodaei andK. Faez, “New adaptive steganographicmethod using least-significant-bit substitution and pixel-value differ- encing,” IET Image Processing, vol. 6, no. 6, pp. 677–686, 2012.

[7] W. Luo, F. Huang, and J. Huang, “A more secure steganography based on adaptive pixel-value differencing scheme,”Multimedia Tools and Applications, vol. 52, no. 2-3, pp. 407–430, 2011.

[8] A. Pradhan, K. R. Sekhar, and G. Swain, “Adaptive PVD Steganography Using Horizontal, Vertical, and Diagonal Edges in Six-Pixel Blocks,” Security andCommunication Networks, vol. 2017, pp. 1–13, 2017.

[9] X. Liao, Q. Wen, and J. Zhang, “A steganographic method for digital images with four-pixel differencing and modified LSB substitution,” Journal of Visual Communication and Image Representation, vol. 22, no. 1, pp. 1–8, 2011.

[10] X. Zhang and S. Wang, “Efficient steganographic embedding by exploiting modification direction,” IEEE Communications Letters, vol. 10, no. 11, pp. 781–783, 2006.

[11] C.-C. Chang, W.-L. Tai, and K.-N. Chen, “Improvements of EMD embedding for large payloads,” in Proceedings of the 3rd International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIHMSP 2007, vol. 1, pp. 473–476, November 2007.

[12] C.-F. Lee, Y.-R. Wang, and C.-C. Chang, “A steganographic method with high embedding capacity by improving exploiting modification direction,” in Proceedings of the 3rd International Conference on Intelligent Information Hiding and Multimedia Signal Processing, pp. 497–500, November 2007.

[13] C.-F. Lee, C.-C. Chang, and K.-H. Wang, “An improvement of EMD embedding method for large payloads by pixel segmenta- tion strategy,” Image and Vision Computing, vol. 26, no. 12, pp. 1670–1676, 2008.

[14] K. H. Jung and K. Y. Yoo, “Improved modification direction technique by modulus operation,” International Journal of Signal Processing, Image Processing and Pattern, vol. 2, no. 1, pp. 79–87, 2009.

[15] R. Chao, H. Wu, C. Lee, and Y. Chu, “A Novel Image Data Hiding Schemewith Diamond Encoding,” EURASIP Journal on Information Security, vol. 2009, no. 1, p. 658047, 2009.

[16] J.-C. Joo, H.-Y. Lee, and H.-K. Lee, “Improved steganographic method preserving pixel-value differencing histogram with modulus function,” Eurasip Journal on Advances in Signal Processing, vol. 2010, Article ID 249826, 2010.

[17] H. J. Kim, C. Kim, S. Wang, and X. Zhang, “Improved mod- ification direction methods,” Computers & Mathematics with Applications, vol. 60, no. 2, pp. 319–325, 2010.

[18] J. Wang, Y. Sun, H. Xu, K. Chen, H. Joong Kim, and S.-H. Joo, “An improved section-wise exploiting modification direction method,” Signal Processing, vol. 90, no. 11, pp. 2954–2964, 2010.

[19] T. D. Kieu and C.-C. Chang, “A steganographic scheme by fully exploiting modification directions,” Expert Systems with Applications, vol. 38, no. 8, pp. 10648–10657, 2011.

[20] X.-T. Wang, C.-C. Chang, C.-C. Lin, and M.-C. Li, “A novel multi-group exploiting modification direction method based on switch map,” Signal Processing, vol. 92, no. 6, pp. 1525–1535, 2012.

[21] D.-S. Fu, Z.-J. Jing, S.-G. Zhao, and J. Fan, “Reversible data hiding based on prediction-error histogram shifting and EMD mechanism,” AEU - International Journal of Electronics and Communications, vol. 68, no. 10, pp. 933–943, 2014.

[22] C. Kim, “Data hiding by an improved exploiting modification direction,”Multimedia Tools and Applications, vol. 69, no. 3, pp. 569–584, 2014.

[23] S.-Y. Shen and L.-H. Huang, “A data hiding scheme using pixel value differencing and improving exploiting modification directions,” Computers and Security, vol. 48, pp. 131–141, 2015.

[24] A. Soria-Lorente and S. Berres, “A Secure Steganographic AlgorithmBased on FrequencyDomain for the Transmission of Hidden Information,” Security and Communication Networks, vol. 2017, pp. 1–14, 2017.

[25] A. Pradhan, K. Raja Sekhar, and G. Swain, “Digital image steganography based on seven way pixel value differencing,” Indian Journal of Science and Technology, vol. 9, no. 37, Article ID 88557, 2016.

Hindawi www.hindawi.com Volume 2018

Journal of

International Journal of Mathematics and Mathematical Sciences

Hindawi www.hindawi.com Volume 2018

The Scientific World Journal

Numerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical Analysis Advances inAdvances in Discrete Dynamics in

Nature and Society Hindawi www.hindawi.com Volume 2018

Hindawi www.hindawi.com

Volume 2018

Anita Pradhan , K. Raja Sekhar, and Gandharba Swain

Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Andhra Pradesh 522502, India

Correspondence should be addressed to Gandharba Swain; gswain1234@gmail.com

Received 29 March 2017; Revised 14 July 2017; Accepted 25 July 2017; Published 5 September 2018

Academic Editor: Julien Bruchon

Copyright © 2018 Anita Pradhan et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

To protect from pixel difference histogram (PDH) analysis and RS analysis, two hybrid image steganography techniques by appropriate combination of LSB substitution, pixel value differencing (PVD), and exploiting modification directions (EMD) have been proposed in this paper. The cover image is traversed in raster scan order and partitioned into blocks. The first technique operates on 2 × 2 pixel blocks and the second technique operates on 3 × 3 pixel blocks. For each block, the average pixel value difference, , is calculated. If value is greater than 15, the block is in an edge area, so a combination of LSB substitution and PVD is applied. If value is less than or equal to 15, the block is in a smooth area, so a combination of LSB substitution and EMD is applied. Each of these two techniques exists in two variants (Type 1 andType 2) with respect to two different range tables.The hiding capacities and PSNR of both the techniques are found to be improved. The results from experiments prove that PDH analysis and RS analysis cannot detect these proposed techniques.

1. Introduction

The fundamental principle of a steganography technique is to hide the secret data in image, audio, or video files [1]. Data can be hidden in images using spatial domain or frequency domain. LSB substitution is the most common technique of data hiding in spatial domain. But it can be easily detected by RS analysis [2]. To augment security in LSB substitution techniques, some precautionary measures need to be taken. The LSB planes that will carry the secret data can be selected based upon the bit pattern hidden in neighboring pixels [3]. The bits from one or more LSB planes of the pixels can be joined together to make an array. The binary data bits can be concealed in this array at appropriate portions to minimize distortion and to improve the security [4]. The PVDsteganography is another familiar data hiding technique [5]. This technique exploits the smooth areas to hide lesser number of secret bits and edge areas to hide more number of secret bits. Many variants of PVD technique have been found in literature. A technique of Khodaei and Faez uses both LSB and PVD concepts [6]. It possesses higher hiding capacity and lesser distortion. The problem in the PVD techniques is

that they are attacked by pixel difference histogram (PDH) analysis. One mechanism that addresses this problem is the adaptive range table [7, 8]. Instead of a fixed range table for all the pixels, it can be varied for every pixel. Even the number of LSB bits to be hidden in different pixels can be varied based on the smoothness of the block into which the pixel belongs to [9], so that security can be improved.

Zhang and Wang [10] proposed exploiting modification direction (EMD) steganography. The principal goal in it is that a group of secret bits be converted to a digit in (2 + 1)- ary notational system, where is the size of pixel block. This secret digit could be hidden in the pixel block by adding ±1 to only one pixel. In this technique, the hiding capacity is not good. The hiding capacity has been improved in two- stage technique in [11] and 8-ary technique in [12]. Lee et al. [13] proposed EMD technique using pixel segmentation. In a pair of pixels, each pixel is segmented into two segments. The MSB segments of the two pixels together is called the vector of coordinates (VCA) and the LSB segments of the two pixels together are called vector modification area (VMA). The bits of VCA decide about embedding. Jung and Yoo [14] proposed an EMD technique in a block of one pixel to

Hindawi Mathematical Problems in Engineering Volume 2018, Article ID 1804953, 11 pages https://doi.org/10.1155/2018/1804953

Pc P1

P2 P3

3

(c)

Figure 1: (a) Cover pixel block, (b) stego block, and (c) stego block used for extraction.

increase the hiding capacity. The EMD technique based on diamond encoding also could improve the hiding capacity [15]. Joo et al.’s EMD technique using modulus function preserved the pixel difference histogram [16]. Kim et al. [17] has proposed two EMD techniques, namely, EMD-2 and 2- EMD. In EMD-2 technique at most two pixels are modified and in 2-EMD technique, two consecutive EMDs are used. Both these techniques achieve higher hiding capacity. Wang et al. [18] said that a number of pixel groups could be combined to derive more number of embedding directions, so that distortion can be reduced. Kieu and Chang’s [19] EMD technique used eight modification directions. It fully exploited allmodification directions andmeasured the hiding capacity and distortion for different values of the parameter, . Wang et al.’s [20] EMD technique combined multiple groups to hide the data according to a designed switch map, so that the hiding capacity can be increased and distortion can be decreased. Fu et al. [21] used EMD and multilayer embedding mechanism with histogram shifting to achieve reversibility. Kim [22] advanced the EMD technique using basis vector, and (2+ − 1)-ary notational system, where and are user defined values. Shen and Huang [23] made the hiding capacity of a block adaptive by using PVD with EMD. This PVD with EMD technique provides higher hiding capacity and better PSNR. To improve upon the security keys are used to generate pseudo random num- bers, which can be used to find the embedding locations [24].

It is found that Shen and Huang’s [23] PVD with EMD technique is detectable by PDH analysis. To advance further in this paper we judiciously combined LSB substitution, PVD, and EMD techniques to protect against PDH analysis and to possess larger hiding capacity without sacrificing the PSNR. There are two techniques proposed, the first technique is designed using 2 × 2 pixel blocks and the second technique is designed using 3 × 3 pixel blocks.

2. The Proposed Technique 1 (LSB + PVD + EMD in 2 × 2 Pixel Blocks)

2.1. The Embedding Procedure

Step 1. The image is traversed in raster scan order and partitioned into nonoverlapping blocks of size 2× 2. A sample block is shown in Figure 1(a).

Step 2. For every block the average pixel value difference, = (1/3)∑3

=1 | − |, is computed. If is greater than 15, then

Table 1: Range table (Type 1).

Range, { , } 1 = {0, 7} 2 =

{8, 15} 3 =

{16, 31} 4 =

{32, 63} 5 =

{64, 127} 6 =

Range, { , } 1 = {0, 7} 2 =

{8, 15} 3 =

{16, 31} 4 =

{32, 63} 5 =

{64, 127} 6 =

3 3 4 5 6 6

the block is said to be an edge area; otherwise, it is a smooth area.

Step 3. In an edge area embedding is done using LSB substitution and PVD.

Step 4. In a smooth area embedding is done using LSB substitution and EMD.

TheLSB + PVDEmbedding Approach. The first LSB of pixel is substituted by bit 1, to act as an indicator during extraction. The other 2 LSBs are substituted by 2 data bits. A new value of this pixel

is obtained. Suppose, the decimal value of the

three LSBs of is 1 and the decimal value of the three LSBs

of is 1. A difference value df1 = 1 − 1 is calculated and

is optimized by

= {{{{ {{{{ {

+ 23, if df1 > 23−1, 0 ≤ ( + 23) ≤ 255 − 23, if df1 < −23−1, 0 ≤ ( − 23) ≤ 255 , otherwise

(1)

Now calculate three difference values, = | − | for = 1, 2, 3. It falls into one of the ranges in range table. Based on the range of , the number of bits to be hidden () can be decided. Table 1 can be referred to as Type 1 and Table 2 can be referred to as Type 2. Now convert each bits of confidential data to its decimal value for = 1, 2, 3. Then compute the new value for this difference as

= + for = 1, 2, 3.

Now for each where = 1, 2, 3, calculate two new values

Mathematical Problems in Engineering 3

= − and

= + . Select one of these two values

as by applying

= { { {

(2)

The LSB + EMD Embedding Approach. The first LSB bit of pixel is substituted by bit 0, which can act as an indicator during extraction. The other two LSBs of are substituted by two data bits. Thus, a new value

of the pixel is obtained.

Suppose, the decimal value of the three LSBs of is 1 and

the decimal value of the three LSBs of is 1. A difference

value df1 = 1 − 1 is calculated and is optimized by

(1). Suppose we denote the remaining pixels (1, 2, 3) by

a name , where = 1, 2, 3. Now apply EMD for each as follows. Each has to hide 2 bits of data. The decimal equivalent of the two data bits is . Now select from {−3, −2, −1, 0} and calculate

= + such that the

condition ( mod 4 = ) satisfies. Similarly select from

{1, 2, 3} and calculate = + such that the condition

(

mod 4 = ) satisfies. If for all the three values in list {1, 2, 3}, the condition (

mod 4 = ) does not satisfy,

then set = −10. Now calculate the stego value

for

, ) ≤ 255, −

, ) ≤ 255, −

2.2. The Extraction Procedure

Step 1. The stego image is traversed in raster scan order and partitioned into nonoverlapping blocks of size 2 × 2. Figure 1(c) represents a sample 2 × 2 stego-pixel block.

Step 2. The LSB bit of ∗ is checked, if it is 1, then for

this block the extraction procedure of LSB + PVD approach is used as follows. The next two LSBs of ∗

are extracted.

Furthermore, the ∗ = |∗ −∗ | and ∗

= ∗ − for = 1, 2, 3

are calculated, where ∗ belongs to the range and is the

lower bound of this range. Now each of these ∗ is converted

to binary bits, where is the value corresponding to the same range of ∗ . Note that the same range table (Table 1 or Table 2) which was used during embedding should be used during extraction.

Step 3. If the LSB bit of ∗ is 0, then for this block the

extraction procedure of LSB + EMD is applied as follows.The next two LSBs of∗

are extracted. For all the remaining pixels

(∗ 1 , ∗ 2 , ∗ 3 ) the decimal equivalent of the embedded bits,,

is calculated as = ∗ mod 4, for = 1, 2, 3. Now each is converted to 2 binary bits.

3. The Proposed Technique 2 (LSB + PVD + EMD in 3 × 3 Pixel Blocks)

3.1. The Embedding Procedure

Step 1. The image is traversed in raster scan order and partitioned into nonoverlapping blocks of size 3× 3. A sample block is shown in Figure 2(a).

Step 2. An average pixel value difference, = (1/8)∑8 =1 | −

|, is calculated.

Step 3. If value is greater than 15, then a combination of LSB substitution and PVD is applied.

Step 4. If value is less than or equal to 15, then a combina- tion of LSB substitution and EMD is applied.

The LSB + PVD Embedding Approach. In the central pixel, 3 LSBs are substituted by 3 data bits. A new value of the central pixel is found. Say it is

. In pixel 8 the first LSB

is substituted by bit 1, which will be used as indicator during extraction procedure.The other two LSBs in it are substituted by two data bits. After substituting, three LSBs, suppose the new value of pixel 8 is 8. The decimal value of the three LSBs of

is 1 and the decimal value of three LSBs of is

1. Similarly, the decimal value of three LSBs of 8 is 2 and

the decimal value of three LSBs of 8 is 2. Now calculate the differences df1 and df2 as, df1 = 1 − 1 and df2 = 2 − 2. Now optimize the values of

and 8 using (1) and (4), respectively.

8 = {{ {{ {

8 + 23, if df2 > 23−1, 0 ≤ (8 + 23) ≤ 255 8 − 23, if df2 < −23−1, 0 ≤ (8 − 23) ≤ 255 8 , otherwise

(4)

Now calculate seven difference values, = | − | for = 1, 2, . . . , 7. These difference values lie in one of the ranges of the range table. Table 1 can be chosen as Type 1 or Table 2 can be chosen as Type 2. Based on the range of , the number of bits to be hidden () can be decided from the range table.

Now convert each bits of confidential data to its decimal value for = 1, 2, . . . , 7. Then compute the new values for the seven differences as

= + for = 1, 2, . . . , 7. Now for

each where = 1, 2, . . . , 7, calculate two new values =

− and

= + . Select one of these two values as

by applying (2). This is the stego value of .

The LSB + EMD Embedding Approach. The first LSB of pixel 8 is substituted by 0 and the next two LSBs are substituted by two data bits. After embedding, say it is

8 . The decimal

Table 3: Results of existing techniques.

Images 512 × 512 × 3

Wu and Tsai [5] Shen and Huang [23] PSNR Capacity BPB PSNR Capacity BPB

Lena 43.67 1232606 0.999 1.56 38.01 1223062 0.998 1.55 Baboon 38.40 1403491 0.998 1.78 40.14 1343274 0.999 1.70 Peppers 43.13 1174751 0.999 1.49 41.57 1226139 0.999 1.55 Jet 43.97 1220544 0.999 1.55 43.35 1212350 0.999 1.54 Boat 41.33 1278971 0.999 1.62 41.35 1264742 0.999 1.60 House 41.27 1256404 0.999 1.59 41.75 1242081 0.999 1.57 Pot 44.01 1163700 0.999 1.47 43.38 1195641 0.999 1.52 Average 42.25 1247209 0.999 1.57 41.36 1243898 0.999 1.58

P4 P3 P2

P5 Pc P1

P6 P7 P8

(c)

Figure 2: (a) Cover pixel block, (b) stego block, and (c) stego block used for extraction.

value of the three LSBs of 8 is 2 and the decimal value of

three LSBs of8 is 2. Now calculate the difference df 2 as df2 = 2 − 2. Now optimize the value of

8 using (4).

Suppose we denote the remaining pixels (1, 2, 3, 4, 5, 6, 7, ) by a name , where = 1, 2, 3, 4, 5, 6, 7, . Now apply EMD for each as follows. Each has to hide 2 bits of data. The decimal equivalent of the two data bits is . Now select from {−3, −2, −1, 0} and calculate

= +

such that the condition ( mod 4 = ) satisfies. Similarly

select from {1, 2, 3} and calculate = + such that

the condition (

mod 4 = ) satisfies. If for all the three values in list {1, 2, 3}, the condition (

mod 4 = ) does

not satisfy, then set = −10. Now calculate

by (3). This

is the stego value of . Thus, Figure 2(b) represents the stego-pixel block.

3.2. The Extraction Procedure

Step 1. The stego image is traversed in raster scan order and partitioned into nonoverlapping blocks of size 3 × 3. Figure 2(c) represents a sample 3 × 3 stego-pixel block.

Step 2. The LSB bit of ∗ 8 is checked, if it is 1 then for this

block the extraction procedure of LSB + PVD approach is used as follows. The three LSBs of ∗

and next two LSBs

of ∗ 8 are extracted. Furthermore, the ∗

= |∗ − ∗ | and

∗ = ∗ − for = 1, 2, 3, . . . , 7 are calculated, where ∗

belongs to the range and is the lower bound of this range. Now each of these ∗

is converted to binary bits, where

is the value corresponding to the same range of ∗ . Note that the same range table (Table 1 or Table 2) which was used during embedding should be used during extraction.

Step 3. If the LSB bit of ∗ 8 is 0, then for this block the

extraction procedure of LSB + EMD is applied as follows.

The next two LSBs of ∗ 8 are extracted. For all the remaining

pixels (∗ 1 , ∗ 2 , ∗ 3 , ∗ 4 , ∗ 5 , ∗ 6 , ∗ 7 , ∗ ), the decimal equivalent

of the embedded bits, is calculated as = ∗ mod 4, for = 1, 2, 3, 4, 5, 6, 7, . Now each is converted to 2 binary bits.

4. Results and Discussion The implementation work is done using MATLAB tool and with the RGB color images. The data hiding is performed in Red, Green, and Blue planes separately. It can also be applied on gray scale images. Experiments are done with many images. Few samples are shown here. Figure 3 represents four original samples. Figures 4 and 5 are their stego samples for Type 1 and Type 2 of technique 1, respectively. Figures 6 and 7 are the stego samples for Type 1 and Type 2 of technique 2, respectively. Each stego image has hidden 700000 (seven lakhs) bits of secret data. These stego images look innocuous and no distortion is observable.

In Table 3 the results of Wu and Tsai’s PVD technique and Shen and Huang’s [23] PVD + EMD technique are given. In Tables 4 and 5, the results of the proposed technique 1 and technique 2 respectively, are given. These results are comprised of four parameters, (i) hiding capacity [1], (ii) bits per byte (BPB) [8], (iii) PSNR [1], and (iv) quality index, [6].

It can be found from Tables 3, 4, and 5 that the hiding capacity and BPB of proposed technique 1 (Type 1 and Type 2) and technique 2 (Type 1 and Type 2) are significantly enhanced as compared to that of Wu and Tsai and Shen and Huang’s techniques. Furthermore, the PSNR of the proposed technique 1 (Type 1 and Type 2) and technique 2 (Type 1 and Type 2) are nearly equal to that of Wu and Tsai and Shen and Huang’s techniques.

Mathematical Problems in Engineering 5

Table 4: Results of proposed technique 1.

Images 512 × 512 × 3

Proposed 3 PVD + 3 LSB + EMD (Type 1) Proposed 3 PVD + 3 LSB + EMD (Type 2) PSNR Capacity BPB PSNR Capacity BPB

Lena 44.45 1631063 0.999 2.07 41.33 1687353 0.999 2.15 Baboon 34.85 1898778 0.997 2.41 32.54 2237194 0.994 2.84 Peppers 40.26 1635779 0.999 2.08 38.73 1693901 0.999 2.15 Jet 42.88 1637898 0.999 2.08 42.04 1702029 0.999 2.16 Boat 38.50 1708242 0.999 2.17 36.09 1840256 0.998 2.34 House 40.23 1691500 0.999 2.15 39.18 1808544 0.998 2.30 Pot 46.35 1599030 0.999 2.03 42.80 1622565 0.999 2.06 Average 41.07 1686041 0.999 2.14 38.95 1798834 0.998 2.28

Table 5: Results of proposed technique 2.

Images 512 × 512 × 3

Proposed 7 PVD + 3 LSB + EMD (Type 1) Proposed 7 PVD + 3 LSB + EMD (Type 2) PSNR Capacity BPB PSNR Capacity BPB

Lena 44.98 1639022 0.999 2.09 41.26 1690031 0.999 2.15 Baboon 34.67 1987328 0.996 2.54 32.49 2338643 0.994 2.98 Peppers 38.14 1640887 0.998 2.09 34.70 1693278 0.997 2.16 Jet 43.00 1647786 0.999 2.10 40.46 1709098 0.998 2.18 Boat 37.76 1740611 0.998 2.22 34.36 1873870 0.997 2.39 House 40.12 1724458 0.998 2.20 38.79 1841047 0.998 2.35 Pot 43.28 1596123 0.999 2.04 38.80 1617011 0.999 2.06 Average 40.28 1710888 0.998 2.18 37.26 1823282 0.998 2.32

(a) Lena (b) Baboon (c) Boat (d) Pot

Figure 3: Original images.

6 Mathematical Problems in Engineering

Figure 5: Stego images of technique 1 (Type 2).

Figure 6: Stego images of technique 2 (Type 1).

Figure 7: Stego images of technique 2 (Type 2).

Table 6: Average results of proposed techniques.

Type BPB PSNR Proposed 3 PVD + 3 LSB + EMD (Type 1) 2.14 41.07 Proposed 7 PVD + 3 LSB + EMD (Type 1) 2.18 40.28 Proposed 3 PVD + 3 LSB + EMD (Type 2) 2.28 38.95 Proposed 7 PVD + 3 LSB + EMD (Type 2) 2.32 37.26

Furthermore, the average performance of the proposed techniques is compared with that of Kieu and Chang’s [19] technique. The average BPB and PSNR for the proposed two techniques is as given in Table 6. Similarly the BPB and PSNR of Kieu and Chang’s technique for different values of the parameter is as given in Table 7. By observing Table 6 we can find that in the proposed techniqueswith BPB values 2.14, 2.18, 2.28, and 2.32, the PSNR values are 41.07, 40.28, 38.95, and 37.26, respectively. By observing Table 7 we can find that

in the Kieu and Chang’s technique with BPB values 1, 2, 3, and 4, the PSNR values are 52.39, 46.74, 40.82, and 34.82, respec- tively. Thus, the PSNR and BPB values of Kieu and Chang’s technique (for = 6, BPB= 2.5, andPSNR=43.29) are slightly better than that of the proposed techniques (BPB = 2.32, and PSNR = 41.07). But there is no experimental evidence that Kieu and Chang’s technique is undetectable by PDH analysis and RS analysis. The proposed techniques are undetectable by PDH analysis; it is experimentally proved in Figures 9 and 10. It is also proved in Figures 11 and 12 that the proposed techniques are undetectable by RS analysis. PSNR and BPB are not only the measuring parameters; security analysis is also another parameter to be taken into consideration while judging the merit of a steganography technique.

Now let us come to security analysis. The PDH analysis diagrams clearly reveal the step effects in Shen and Huang’s technique, Figures 8(a) and 8(b). Wu and Tsai’s technique is also detected by PDH analysis, proved in [25]. But for

Mathematical Problems in Engineering 7

−40 −20 0 20 40

Pixel difference

Pixel difference

Figure 8: PDH analysis for Shen and Huang’s technique.

−40 −20 0 20 40

Pixel difference

−40 −20 0 20 40

Pixel difference

−40 −20 0 20 40

Pixel difference

−40 −20 0 20 40

Pixel difference

(d) Proposed 3 PVD + 3 LSB + EMD (Type 2)

Figure 9: PDH analysis for proposed technique 1 (Type 1 and Type 2).

8 Mathematical Problems in Engineering

−40 −20 0 20 40

Pixel difference

−40 −20 0 20 40

Pixel difference

−40 −20 0 20 40

Pixel difference

−40 −20 0 20 40

Pixel difference

(d) Proposed 7 PVD + 3 LSB + EMD (Type 2)

Figure 10: PDH analysis for proposed technique 2 (Type 1 and Type 2).

Table 7: Average results of Kieu and Chang’s technique [19].

value BPB PSNR 2 1 52.39 3 1.5 49.89 4 2 46.74 6 2.5 43.29 8 3 40.82 12 3.5 37.31 16 4 34.82 23 4.5 31.69

the proposed techniques, Figures 9(a)–9(d) and Figures 10(a)–10(d), the step effects are not observable.

We can observe the RS analysis curves of the proposed technique 1 in Figure 11. In Lena image there is bigger number of smooth blocks, but in Baboon image there is bigger number of edge blocks. For Baboon image curves for and − are linear and nearly parallel to each other.

Similarly, curves for and − are linear and nearly parallel to each other. Hence, the relation ≅ − > ≅ − is strongly satisfied. For Lena image curve for is linear and the curve for − is slightly diverging from it. Similarly, curves for are linear and the curve for − is slightly diverging from it. Hence, the relation ≅ − > ≅ − is weakly satisfied for Lena image. Figure 12 represents the RS analysis for technique 2. In all the four cases, the graphs for and − are linear and nearly overlap with one another, and the graphs for and − are linear and nearly overlap with one another. Hence, the relation ≅ − > ≅ − is strongly satisfied. Hence, it can be concluded that RS analysis cannot detect the proposed steganography techniques.

5. Conclusion

Shen and Huang proposed PVD in connection with EMD to achieve greater hiding capacity and higher PSNR. But it is found to be detectable by pixel difference histogram analysis.

Mathematical Problems in Engineering 9

50

45

40

35

30

25

20

Percentage of hiding capacity

Percentage of hiding capacity

Percentage of hiding capacity

Percentage of hiding capacity

(d) Baboon (Type 2)

Figure 11: RS analysis for Proposed technique 1 (Type 1 and Type 2).

To fix this problem, a combination of LSB substitution, PVD, and EMD is proposed in this paper. The proposed technique 1 and technique 2 operate on 2 × 2 and 3 × 3 pixel blocks, respectively, by calculating the average of the pixel value differences. Based on this average value, either PVD or EMD

is applied in combination with LSB. Both the techniques give higher hiding capacity compared to that of Shen and Huang’s technique. The recorded PSNR values are also as good as that of Shen and Huang’s technique. If we compare between the two proposed techniques, then Type 1 of technique 1 is

10 Mathematical Problems in Engineering

50

45

40

35

30

25

20

Percentage of hiding capacity

Percentage of hiding capacity

Percentage of hiding capacity

Percentage of hiding capacity

(d) Baboon (Type 2)

Figure 12: RS analysis of Proposed for proposed technique 2 (Type 1 and Type 2).

good for PSNR and Type 2 of technique 2 is good for hiding capacity. It has also been proved that the proposed techniques are not detectable by RS analysis.

Conflicts of Interest

The authors declare that they have no conflicts of interest.

References

[1] A. Cheddad, J. Condell, K. Curran, and P. Mc Kevitt, “Digital image steganography: survey and analysis of current methods,” Signal Processing, vol. 90, no. 3, pp. 727–752, 2010.

[2] J. Fridrich,M.Goljan, andR.Du, “Detecting LSB steganography in color and gray-scale images,” IEEEMultimediaMagazine, vol. 8, no. 4, pp. 22–28, 2001.

Mathematical Problems in Engineering 11

[3] G. Swain and S. K. Lenka, “A technique for secret communi- cation using a new block cipher with dynamic steganography,” International Journal of Security and its Applications, vol. 6, no. 2, pp. 1–12, 2012.

[4] G. Swain and S. K. Lenka, “A novel steganography technique by mapping words with LSB array,” International Journal of Signal and Imaging Systems Engineering, vol. 8, no. 1-2, pp. 115–122, 2015.

[5] D.-C.Wu andW.-H. Tsai, “A steganographicmethod for images by pixel-value differencing,” Pattern Recognition Letters, vol. 24, no. 9-10, pp. 1613–1626, 2003.

[6] M.Khodaei andK. Faez, “New adaptive steganographicmethod using least-significant-bit substitution and pixel-value differ- encing,” IET Image Processing, vol. 6, no. 6, pp. 677–686, 2012.

[7] W. Luo, F. Huang, and J. Huang, “A more secure steganography based on adaptive pixel-value differencing scheme,”Multimedia Tools and Applications, vol. 52, no. 2-3, pp. 407–430, 2011.

[8] A. Pradhan, K. R. Sekhar, and G. Swain, “Adaptive PVD Steganography Using Horizontal, Vertical, and Diagonal Edges in Six-Pixel Blocks,” Security andCommunication Networks, vol. 2017, pp. 1–13, 2017.

[9] X. Liao, Q. Wen, and J. Zhang, “A steganographic method for digital images with four-pixel differencing and modified LSB substitution,” Journal of Visual Communication and Image Representation, vol. 22, no. 1, pp. 1–8, 2011.

[10] X. Zhang and S. Wang, “Efficient steganographic embedding by exploiting modification direction,” IEEE Communications Letters, vol. 10, no. 11, pp. 781–783, 2006.

[11] C.-C. Chang, W.-L. Tai, and K.-N. Chen, “Improvements of EMD embedding for large payloads,” in Proceedings of the 3rd International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIHMSP 2007, vol. 1, pp. 473–476, November 2007.

[12] C.-F. Lee, Y.-R. Wang, and C.-C. Chang, “A steganographic method with high embedding capacity by improving exploiting modification direction,” in Proceedings of the 3rd International Conference on Intelligent Information Hiding and Multimedia Signal Processing, pp. 497–500, November 2007.

[13] C.-F. Lee, C.-C. Chang, and K.-H. Wang, “An improvement of EMD embedding method for large payloads by pixel segmenta- tion strategy,” Image and Vision Computing, vol. 26, no. 12, pp. 1670–1676, 2008.

[14] K. H. Jung and K. Y. Yoo, “Improved modification direction technique by modulus operation,” International Journal of Signal Processing, Image Processing and Pattern, vol. 2, no. 1, pp. 79–87, 2009.

[15] R. Chao, H. Wu, C. Lee, and Y. Chu, “A Novel Image Data Hiding Schemewith Diamond Encoding,” EURASIP Journal on Information Security, vol. 2009, no. 1, p. 658047, 2009.

[16] J.-C. Joo, H.-Y. Lee, and H.-K. Lee, “Improved steganographic method preserving pixel-value differencing histogram with modulus function,” Eurasip Journal on Advances in Signal Processing, vol. 2010, Article ID 249826, 2010.

[17] H. J. Kim, C. Kim, S. Wang, and X. Zhang, “Improved mod- ification direction methods,” Computers & Mathematics with Applications, vol. 60, no. 2, pp. 319–325, 2010.

[18] J. Wang, Y. Sun, H. Xu, K. Chen, H. Joong Kim, and S.-H. Joo, “An improved section-wise exploiting modification direction method,” Signal Processing, vol. 90, no. 11, pp. 2954–2964, 2010.

[19] T. D. Kieu and C.-C. Chang, “A steganographic scheme by fully exploiting modification directions,” Expert Systems with Applications, vol. 38, no. 8, pp. 10648–10657, 2011.

[20] X.-T. Wang, C.-C. Chang, C.-C. Lin, and M.-C. Li, “A novel multi-group exploiting modification direction method based on switch map,” Signal Processing, vol. 92, no. 6, pp. 1525–1535, 2012.

[21] D.-S. Fu, Z.-J. Jing, S.-G. Zhao, and J. Fan, “Reversible data hiding based on prediction-error histogram shifting and EMD mechanism,” AEU - International Journal of Electronics and Communications, vol. 68, no. 10, pp. 933–943, 2014.

[22] C. Kim, “Data hiding by an improved exploiting modification direction,”Multimedia Tools and Applications, vol. 69, no. 3, pp. 569–584, 2014.

[23] S.-Y. Shen and L.-H. Huang, “A data hiding scheme using pixel value differencing and improving exploiting modification directions,” Computers and Security, vol. 48, pp. 131–141, 2015.

[24] A. Soria-Lorente and S. Berres, “A Secure Steganographic AlgorithmBased on FrequencyDomain for the Transmission of Hidden Information,” Security and Communication Networks, vol. 2017, pp. 1–14, 2017.

[25] A. Pradhan, K. Raja Sekhar, and G. Swain, “Digital image steganography based on seven way pixel value differencing,” Indian Journal of Science and Technology, vol. 9, no. 37, Article ID 88557, 2016.

Hindawi www.hindawi.com Volume 2018

Journal of

International Journal of Mathematics and Mathematical Sciences

Hindawi www.hindawi.com Volume 2018

The Scientific World Journal

Numerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical Analysis Advances inAdvances in Discrete Dynamics in

Nature and Society Hindawi www.hindawi.com Volume 2018

Hindawi www.hindawi.com

Volume 2018

Related Documents